University course timetabling using hybridized artificial bee colony with hill climbing optimizer |
| |
| Institution: | 1. School of Computer Sciences, Universiti Sains Malaysia, Penang, Malaysia;2. Department of Computer Science, University of Ilorin, Ilorin, Nigeria;3. Department of Information Technology, Al-Huson University College, Al-Balqa Applied University, P.O. Box 50, Al-Huson, Irbid, Jordan;1. Section of Operations Research, Department of Management Engineering, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark;2. MaCom A/S, Vesterbrogade 48, 1., DK-1620 Copenhagen V, Denmark;3. Chair of Operations Research, RWTH Aachen University, Kackertstrasse 7, 52072 Aachen, Germany;1. Computing and Systems Department, Federal University of Ouro Preto, Brazil;2. Computing Department, Federal University of Ouro Preto, Brazil;1. Software Engineering Research Group, Software Engineering Department, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia;2. Department of Computer Science, Queen’s University Belfast, Belfast BT7 1NN, United Kingdom;3. Department of Electronic, Information and Communication Engineering, Osaka Institute of Technology, Osaka 535-8585, Japan;1. Department of Software Engineering, Faculty of Science and Information Technology, Jadara University, Irbid, Jordan;2. Data Mining and Optimization Research Group (DMO) Center for Artificial Intelligence Technology, Universiti Kebangsaan Malaysia, Selangor, Bangi 43600, Malaysia;1. Department of Mathematics and CMA, Universidade Nova de Lisboa, Portugal;2. School of Computer Science, University of Nottingham, Nottingham, UK |
| |
| Abstract: | University course timetabling is concerned with assigning a set of courses to a set of rooms and timeslots according to a set of constraints. This problem has been tackled using metaheuristics techniques. Artificial bee colony (ABC) algorithm has been successfully used for tackling uncapaciated examination and course timetabling problems. In this paper, a novel hybrid ABC algorithm based on the integrated technique is proposed for tackling the university course timetabling problem. First of all, initial feasible solutions are generated using the combination of saturation degree (SD) and backtracking algorithm (BA). Secondly, a hill climbing optimizer is embedded within the employed bee operator to enhance the local exploitation ability of the original ABC algorithm while tackling the problem. Hill climbing iteratively navigates the search space of each population member in order to reach a local optima. The proposed hybrid ABC technique is evaluated using the dataset established by Socha including five small, five medium and one large problem instances. Empirical results on these problem instances validate the effectiveness and efficiency of the proposed algorithm. Our work also shows that a well-designed hybrid technique is a competitive alternative for addressing the university course timetabling problem. |
| |
| Keywords: | Artificial bee colony Timetabling problem Nature-inspired computing Swarm intelligence Hybrid metaheuristic |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
